A MEMS-based stiffness/energy sensor for structural health prognostics

用于结构健康预测的基于 MEMS 的刚度/能量传感器

• 批准号: 0097509
• 负责人: Abhijit Dasgupta
• 金额: $ 20万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-09-15 至 2005-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0097509&HistoricalAwards=false
• 关键词: MEMS; based; stiffness; energy; sensor

The mechanical state of structures need to be monitored for a variety of reasons, including health diagnostics and health prognostics. The task of identifying the location and nature of damage initiation and growth is made difficult by limitations of (i) sensor technologies and (ii) sensor densities; that can be achieved in realistic structures. Current technologies for mechanical sensors mostly focus on measuring deformations or stains, and are thus useful for deformation-based failure prediction models. In this study we propose to develop a novel class of MEMS-based, self-sufficient sensors that will make direct in-situ measurements of instantaneous local strain, stress, stiffness and energy density in the host structure. Specifically, we have proposed to: (a) provide proof-of-concept of the basic principles for a novel and completely new stiffness/energy sensor; (b) demonstrate a MEMS implementation of the underlying principles; and (c) demonstrate its application for damage/degradation modeling by mounting it externally to structural coupons. It is anticipated that this study will demonstrate and deliver the first working version of a fully autonomous sensor that will provide real-time, in-situ measurements of the changes in a structure's local stiffness and strain energy density. In conjunction with the damage models to be developed during this study, this sensor will provide the first real opportunity to perform real-time health prognostics in complex structures, experiencing complex dynamic loading throughout their life-cycle.

结构的机械状态需要监测的原因有很多，包括健康诊断和健康诊断学。 由于传感器技术和传感器密度的限制，识别损伤起始和增长的位置和性质的任务变得困难;这可以在现实结构中实现。目前的机械传感器技术主要集中在测量变形或应变，因此对于基于变形的故障预测模型是有用的。在这项研究中，我们建议开发一类新的基于MEMS的，自给自足的传感器，将直接在现场测量的瞬时局部应变，应力，刚度和能量密度的主机结构。具体来说，我们提议：（a）为新型全新刚度/能量传感器提供基本原理的概念验证;（B）演示基本原理的MEMS实现;（c）通过将其安装在结构试样外部来演示其在损伤/退化建模中的应用。预计这项研究将展示并提供第一个工作版本的全自主传感器，该传感器将提供对结构局部刚度和应变能密度变化的实时原位测量。 结合本研究期间开发的损伤模型，该传感器将提供第一个真实的机会，在复杂结构中执行实时健康预测，在其整个生命周期中经历复杂的动态载荷。